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公开(公告)号：US20230144585A1
公开(公告)日：2023-05-11
申请号：US17524020
申请日：2021-11-11
发明人： Shubhi Asthana , Shikhar Kwatra , Sushain Pandit
CPC分类号： G06F9/44536 , G06N20/00 , G06K9/6202 , G06K9/6215 , G06K9/623
摘要： Systems, methods, and computer programming products for versioning machine learning models. Changes between new and existing datasets are detected, quantified and compared using statistical and semantic feature comparisons. Recommendations for versioning existing models are in response to detecting changes between the feature importance of datasets used in the application of the machine learning model and new datasets that introduce new features or features that evolve over time in such a manner that feature importance has shifted away from one or more features of the first dataset to the new dataset. Based on the changes in feature importance, statistical changes and semantic feature comparisons, the recommendations provided describe whether models should be updated with a re-trained model, or that the existing features of the model do not indicate a need for re-training.
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公开(公告)号：US20220318522A1
公开(公告)日：2022-10-06
申请号：US17221917
申请日：2021-04-05
发明人： Christine T. Wolf , Jeanette Blomberg , Pravar Mahajan , Shubhi Asthana , Aly Megahed , Pei Guo , Shikhar Kwatra
IPC分类号： G06F40/40 , G06N3/08 , G06N3/04 , G06F40/279 , G06F40/30 , G06F40/166
摘要： Systems and methods for generating user-centric and event-sensitive text summaries are described. For example, summaries may be generated based on user selected reading parameters and user workflow. According to some embodiments, a reinforcement learning module is used to modify a change summarization network based on user feedback. For example, a text summary may change in real-time based on changes to the reader or event context. In some cases, user actions and feedback (e.g., a number of edits to a text summary or the editing time taken by a user) are used to improve prediction of future summaries.
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公开(公告)号：US11295257B2
公开(公告)日：2022-04-05
申请号：US15954754
申请日：2018-04-17
摘要： A system for cognitive prioritization for report generation may include a processor and a memory cooperating therewith. The processor may be configured to accept a request for a new report from a user, the request having a user profile importance associated therewith and generate a predicted completion time for the new report based upon a historical completion time prediction model based upon historical data for prior reports. The processor may be configured to generate a predicted importance of the new report based upon a historical importance prediction model based upon the historical data for prior reports and determine a combined predicted importance based upon the user profile importance and the predicted importance. The processor may also be configured to generate a prioritization of the new report among other reports based upon the predicted completion time and the combined predicted importance and generate the new report based upon the prioritization.
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公开(公告)号：US10742037B2
公开(公告)日：2020-08-11
申请号：US16025988
申请日：2018-07-02
发明人： Hovey R. Strong, Jr. , Raphael I. Arar , Kevin P. Roche , Eric K. Butler , Sandeep Gopisetty , Manuel Hernandez , Pawan R. Chowdhary , Shubhi Asthana , Cheryl A. Kieliszewski
摘要： A computer-implemented method, according to one embodiment, includes: receiving an energy consumption profile which spans multiple intervals in a period of time, and predicting a net energy demand of a consumer system over the period of time. Moreover, a first multiple is determined which, when applied to the received energy consumption profile, produces an updated energy consumption profile which corresponds to an amount of energy that is capable of satisfying the predicted net energy demand of the consumer system. A greatest amount of underprediction is estimated. A greatest amount of overprediction is also estimated. Furthermore, an initial state of an energy storage device electrically coupled to the consumer system is computed according to the updated energy consumption profile. The initial state of the energy storage device is also based on a second multiple applied to each of the greatest amount of underprediction, and the greatest amount of overprediction.
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公开(公告)号：US11631497B2
公开(公告)日：2023-04-18
申请号：US15993381
申请日：2018-05-30
发明人： Shubhi Asthana , Aly Megahed , Hovey R. Strong, Jr. , Samir Tata
摘要： Systems, methods, and computer program products for providing personalized recommendations of devices for monitoring and/or managing a health condition are disclosed, and generally include receiving first structured information regarding a patient and a first set of one or more patient populations; receiving unstructured information regarding at least the patient and a second set of one or more patient populations; analyzing the unstructured information to derive second structured information; determining one or more health metrics to be monitored for the patient based on analyzing each of the first structured information and the second structured information, using a classification model; and determining an optimum set of devices to be used for monitoring the one or more health metrics. In some embodiments, metrics may be continuously monitored to detect a change exceeding an event trigger threshold, and a new set of recommended devices may be generated.
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公开(公告)号：US11341394B2
公开(公告)日：2022-05-24
申请号：US16520851
申请日：2019-07-24
发明人： Heiko H. Ludwig , Hogun Park , Mu Qiao , Peifeng Yin , Shubhi Asthana , Shun Jiang , Sunhwan Lee
摘要： Embodiments relate to systematic explanation of neural model behavior and effective deduction of its vulnerabilities. Input data is received for the neural model and applied to the model to generate output data. Accuracy of the output data is evaluated with respect to the neural model, and one or more neural model vulnerabilities are identified that correspond to the output data accuracy. An explanation of the output data and the identified one or more vulnerabilities is generated, wherein the explanation serves as an indicator of alignment of the input data with the output data.
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公开(公告)号：US20210027133A1
公开(公告)日：2021-01-28
申请号：US16520851
申请日：2019-07-24
发明人： Heiko H. Ludwig , Hogun Park , Mu Qiao , Peifeng Yin , Shubhi Asthana , Shun Jiang , Sunhwan Lee
IPC分类号： G06N3/04 , G06N5/04 , G06K9/62 , G06F16/901
摘要： Embodiments relate to systematic explanation of neural model behavior and effective deduction of its vulnerabilities. Input data is received for the neural model and applied to the model to generate output data. Accuracy of the output data is evaluated with respect to the neural model, and one or more neural model vulnerabilities are identified that correspond to the output data accuracy. An explanation of the output data and the identified one or more vulnerabilities is generated, wherein the explanation serves as an indicator of alignment of the input data with the output data.
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公开(公告)号：US20200050993A1
公开(公告)日：2020-02-13
申请号：US16102622
申请日：2018-08-13
发明人： Shubhi Asthana , Valeria Becker , Aly Megahed , Michael E. Rose , Brian D. Yost , Taiga Nakamura , Hovey R. Strong, JR.
摘要： A computer-implemented method, according to one embodiment, includes: receiving an offer request including one or more desired services, and selecting available offerings, each of which include at least one of the desired services. A determination is made whether available benchmarks exist for each of the at least one desired service included in each of the selected available offerings. For each desired service determined as not having available benchmarks, a draft benchmark is computed for each of a plurality of criteria. A confidence weight is also computed for each of the draft benchmarks. The available benchmarks, the draft benchmarks, and the confidence weights are further used to construct an offer which is submitted in response to the received offer request. Moreover, the draft benchmarks and the corresponding confidence weights are re-computed for each of the respective desired services in response to determining that the submitted offer was not accepted.
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公开(公告)号：US20230123399A1
公开(公告)日：2023-04-20
申请号：US17500994
申请日：2021-10-14
发明人： Shikhar Kwatra , ALY MEGAHED , Shubhi Asthana , Indervir Singh Banipal , MOHAMED MOHAMED , Hovey Raymond Strong , SAMIR TATA
摘要： A computer implemented method for selecting service providers includes receiving a set of client requirements and analyzing available service providers based on the received set of client requirements. The method additionally includes scoring the available service providers based on the analysis. The method further includes identifying one or more unstructured external data sources corresponding to the available service providers and analyzing the reliability of the one or more unstructured external data sources with respect to the available service providers. The method further includes adjusting the scoring of the service providers based, at least in part, on the data source reliability, and subsequently providing an optimal selection of service providers based on the adjusted scoring. A computer program product and computer system corresponding to the method are also disclosed.
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公开(公告)号：US20220270019A1
公开(公告)日：2022-08-25
申请号：US17184327
申请日：2021-02-24
IPC分类号： G06Q10/06 , G06Q10/00 , G06Q10/10 , G06F16/245
摘要： Embodiments are provided for ticket-agent matching and agent skillset development. In some embodiments, a system includes a processor that executes computer-executable components stored in memory. The computer-executable components can include a matching component that determines, using a ticket profile and a space of agent profiles, a ticket-agent pair including a ticket identifier of a service request and an agent identifier of a particular agent within a pool of agents. The computer-executable components also can include a rematching component that assigns a second agent identifier to the service request to develop a skillset of a second particular agent within the pool of agents, the second agent identifier being associated with an unsatisfactory skill score for a defined skill to resolve the service request.
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